first set of filters.

filters.py

@@ -1,15 +1,108 @@
-from PIL import ImageEnhance
+import cv2
+import numpy as np
+from PIL import Image
 
 def apply_filters(image):
-    filters = []
+    filtered_images = []
 
-    # Filter 1: Brightness boost
-    filters.append(ImageEnhance.Brightness(image).enhance(1.3))
+    # Filter 1: Contrast adjustment
+    filtered_images.append(adjust_contrast(image))
 
-    # Filter 2: Contrast boost
-    filters.append(ImageEnhance.Contrast(image).enhance(1.5))
+    # Filter 2: Saturation boost
+    filtered_images.append(adjust_saturation(image))
 
-    # Filter 3: Color boost
-    filters.append(ImageEnhance.Color(image).enhance(1.8))
+    # Filter 3: Exposure adjustment
+    filtered_images.append(adjust_exposure(image))
 
-    return filters
+    # Filter 4: Denoised
+    filtered_images.append(denoise_image(image))
+
+    # Filter 5: Vignette effect
+    filtered_images.append(apply_vignette(image))
+
+    return filtered_images
+
+def adjust_contrast(image, alpha=1.5):
+    """
+    Adjusts the contrast of the image.
+    :param image: Input image (numpy array).
+    :param alpha: Contrast control (1.0-3.0). 1.0 means no change.
+    :return: Contrast adjusted image.
+    """
+    return cv2.convertScaleAbs(image, alpha=alpha, beta=0)
+
+def adjust_saturation(image, saturation_scale=1.0):
+    """
+    Adjusts the saturation of the image.
+    :param image: Input image (numpy array).
+    :param saturation_scale: Saturation scale factor. 1.0 means no change.
+    :return: Saturation adjusted image.
+    """
+    hsv_img = cv2.cvtColor(image, cv2.COLOR_BGR2HSV).astype(np.float32)
+    hsv_img[:, :, 1] *= saturation_scale
+    hsv_img[:, :, 1] = np.clip(hsv_img[:, :, 1], 0, 255)
+    return cv2.cvtColor(hsv_img.astype(np.uint8), cv2.COLOR_HSV2BGR)
+
+def adjust_exposure(image, beta=50):
+    """
+    Adjusts the exposure (brightness) of the image.
+    :param image: Input image (numpy array).
+    :param beta: Brightness control. Positive values increase brightness, negative decrease.
+    :return: Exposure adjusted image.
+    """
+    return cv2.convertScaleAbs(image, alpha=1.0, beta=beta)
+
+def denoise_image(image, h=10):
+    """
+    Denoises the image using Non-local Means Denoising algorithm.
+    :param image: Input image (numpy array).
+    :param h: Filter strength. Higher h value removes noise better but removes details.
+    :return: Denoised image.
+    """
+    return cv2.fastNlMeansDenoisingColored(image, None, h, h, 7, 21)
+
+def crop_image(image, x, y, width, height):
+    """
+    Crops the image to the specified rectangle.
+    :param image: Input image (numpy array).
+    :param x: Top-left x-coordinate.
+    :param y: Top-left y-coordinate.
+    :param width: Width of the crop rectangle.
+    :param height: Height of the crop rectangle.
+    :return: Cropped image.
+    """
+    return image[y:y+height, x:x+width]
+
+def apply_vignette(image, level=2):
+    """
+    Applies a vignette effect to the image.
+    :param image: Input image (numpy array).
+    :param level: Intensity of the vignette effect.
+    :return: Image with vignette effect applied.
+    """
+    rows, cols = image.shape[:2]
+    kernel_x = cv2.getGaussianKernel(cols, cols/level)
+    kernel_y = cv2.getGaussianKernel(rows, rows/level)
+    kernel = kernel_y * kernel_x.T
+    mask = kernel / kernel.max()
+    vignette = np.copy(image)
+    for i in range(3):
+        vignette[:, :, i] = vignette[:, :, i] * mask
+    return vignette
+
+if __name__ == "__main__":
+    # Load a test image
+    test_image = Image.open("toa-heftiba-Xmn-QXsVL4k-unsplash.jpg")
+    # Convert PIL Image to numpy array (BGR format for OpenCV)
+    test_image_np = np.array(test_image)
+    test_image_np = cv2.cvtColor(test_image_np, cv2.COLOR_RGB2BGR)
+    
+    # Apply all filters
+    filtered_images = apply_filters(test_image_np)
+    
+    # Save results
+    for i, filtered_img in enumerate(filtered_images):
+        # Convert back to RGB for saving
+        rgb_img = cv2.cvtColor(filtered_img, cv2.COLOR_BGR2RGB)
+        Image.fromarray(rgb_img).save(f"filter_{i+1}_result.jpg")
+        print(f"Saved filter_{i+1}_result.jpg")